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Relationship between meteorological measurements and flowering of index species to flowering of 53 plant species
Agricultural Meteorology, 20(1979) 189--204
189
©Elsevier Scientific Publishing Company, Amsterdam -- Printed in The Netherlands
RELATIONSHIP BETWI~EN METEOROLOGICAL MEASUREMENTS FLOWERING OF INDEX SPECIES TO FLOWERING OF 53 PLANT SPECIES*
AND
L A R R Y M. WHITE
Range Scientist, USDA-SEA, Agricultural Research, Northern Plains Soil and Water Research Center, Sidney, Montana 59270 (U.S.A.) (Received January 5, 1978; accepted after revision April 28, 1978) ABSTRACT White, L. M., 1979. Relationship between meteorological measurements and flowering of index species to flowering of 53 plant species. Agric. Meteorol., 20: 189--204. Agriculturists and range managers need advanced knowledge o f when a plant will reach a specific developmental stage to plan when to apply herbicides, to begin grazing season, to change pastures in a grazing system, and to harvest forage. Relationship between flowering dates of 53 plant species and accumulation of temperature, temperature plus solar radiation, and the flowering of index species was studied for four years near Sidney, Montana Accumulation o f thermal days (a nonlinear heat unit system which discounts mean temperatures over an o p t i m u m ) was the most accurate of eleven methods tested in accounting for variation among flowering dates. It accounted for 49% of the variation for early-flowering species but only accounted for 34% of the variation for late-flowering species. However, the degree days (remainder) was simpler to calculate and resulted in only 0.3-day standard deviation (SD) loss of accuracy. The degree days (remainder) was equal with the degree hours (duration-summation) in accuracy and both were a day more accurate than the NOAA-degree days. The 20-day moving average of m ax i m u m air temperatures was the least accurate of the eleven methods in accounting for variation of flowering dates. The addition o f solar-radiation with temperature did not account for any more o f the variation among flowering dates. The date that a selected index species flowered was the simplest and probably the most practical method of estimating flowering dates if a 1.0 day (SD) loss of accuracy was acceptable. Knowing the time that a selected index species flowered made possible estimating within five days (SD) the flowering dates of 40 species one to three months earlier.
INTRODUCTION Phenology (the science concerned with the relationship of periodic biological events with seasonal climatic changes) can assist agriculturists and range managers in making management decisions. With advance knowledge of when plant species will reach a specific developmental stage, plans can be *Contribution: USDA-SEA, Agricultural Research, NorthernPlains Soiland Water Research Center, in cooperationwith the Montana Agricultural ExperimentStation, Journal Series No. 799.
190
made to: (1) apply herbicides; (2) begin grazing season; (3) change pastures in a grazing system; and (4) harvest forage. Plant flowering, the developmental stage considered herein, is undoubtedly affected by the entire soil and aerial environment. However, temperature largely controls plant growth and development (Wielgolaski, 1974). The summation of positive temperatures or heat units (degree days) (remainder) above a threshold or "base temperature" has been used for many years to determine maturity date of cultivated plants (Holmes and Robertson, 1959). The degree days (remainder) under calculates degree days when the minimum temperature is below the threshold temperature. Various methods have been developed to correct this error (Lindsey and Newman, 1956; Gilmore and Rogers, 1958; Arnold, 1960). The degree days (remainder) also assumes a linear relationship between plant development and all temperatures above the threshold temperature. Changing the threshold thus changes the weight of each degree above the threshold and does not recognize an optimum temperature for plant development. Various methods have been developed to discount high temperatures and recognize an optimum temperature (Madariaga and Knott, 1951; Gilmore and Rogers, 1958; Brown, 1960). Few studies have been conducted that related the accumulation of temperature to growth and development of North American plant species. Lindsey and Newman (1956) found that flowering of 24 species near Bluffton, Indiana, was closely related to degree days (remainder). However, they had to vary the threshold temperature between 5 and 10°C, depending on the species. Blaisdell (1958), working near Dubois, Idaho, found that the mean March-through-May temperature was highly correlated with flowering of eight species. Bassett et al. (1961) found that flowering of some species near Ottawa, Ontario, was related to variation in average maximum air temperature, others to variation in average minimum air temperatures, still others were not markedly influenced by air temperature. Several studies reported on the average flowering dates for many North American plant species, but they have not attempted to relate meteorological measurements to plant development (Smith, 1915; Criddle, 1927; Leopold and Jones, 1947; Stevens, 1956; Budd and Campbell, 1959; Hulbert, 1963). The objective of this study was to determine the relationship between temperature, temperature plus solar radiation, and flowering of index plant species to flowering of 53 plant species during four years. M A T E R I A L S AND METHODS
The study was conducted on a mixed-prairie, glaciated-plains, sandy-range site on a Williams loam soil (fine-loamy mixed, Typic Axgiborolls) 4 km northwest of Sidney, Montana at an elevation of 665 m. The study site was a uniform area 100 by 100 m that gently sloped to the southwest. Frost-free period averages 122 days; January and July average temperatures are --13 and 20°C, respectively. Average annual precipitation is 34 cm, 44% of which
191
occurs during April through June when most native species make their greatest growth. For the s t u d y years (1967, 1968, 1969, 1971), the total Aprilthrough-June precipitation departed from normal by 6, --1, 8 and --2 cm, respectively. Each year, the s t u d y site was visited three or four times weekly from April through August and the flowering dates of 53 selected native range species were recorded (Table I). Forbs and shrubs were considered as flowering when 10% of the plants within the study area had at least one flower. Grasses and sedges were considered as flowering when 10% of their first heads were fully visible. Heading was used for grasses and sedges, rather than anthesis, as the criterion, because some species, like needleandthread and green needlegrass, self-pollinate and anthers never become visible. Maximum and minimum shelter temperatures and precipitation were obtained at the site. Solar radiation data were taken from official records for Glasgow, Montana, the nearest location (190 km west-northwest of the site). The climate resembles that at Sidney, elevation is only 34 m higher, and although daily solar radiation varies somewhat, only small errors should be introduced in the calculations. Flowering dates were separately related to nine different ways of accumulating daily meteorological measurements from the first of March each year. The first method, was the 20-day moving average of maximum air temperatures. The second method, degree days (remainder) was the simple accumulation of daily mean air temperatures above a given threshold (linear temperature response). The third method, degree hours (duration-summation) (Lindsey and Newman, 1956) was the accumulation of degree hours (DH) and when the minimum temperature (Tmin) was less than the threshold temperature (Tthre), they were calculated by eq.l: DH
=
12 (Tmax -- Tthre) 2 T m a x - Tmin
(1)
where Tmax = m a x i m u m temperature (linear temperature response). When the minimum temperature was equal or greater than the threshold temperature, degree hours (duration-summation) were calculated by eq.2: DH
=
24 (Tmax-2 Tmin)__ ~ Tthre
(2)
The fourth method, called "NOAA-degree days" is the method used to calculate degree days in the National Weekly Weather and Crop Bulletin that is published by the United States Department of Agriculture and the National Oceanic and Atmospheric Administration (NOAA). This m e t h o d accumulates the degrees that the mean temperature was above the threshold temperature with t w o exceptions (non-linear temperature response). Exception 1 was when the minimum temperature was below the threshold, the minimum was
~D b~
TABLE I Average, earliest and latest flowering dates of 53 plant species for 4 years near Sidney, Montana Plant No.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 I9 20 21 22 23 24 25 26 27
Scientific name
C o m m o n name
Average flowering date
Earliest flowering date
Latest flowering date
Carex filifolia Carex heliophila Carex eleocharis Phlox hoodii Taraxacu m o fficina le Astragalusmi~ouriensis Viola nuttallii Arabis holboellii Sy~nga vuigaris Erysimum asperum Astragalus pectinatus Alliumtextile Oxytropis lambertii Koeleria cristata Penstemon albidus Stipa comata Tragopogon dubius Poa pratensis Gaura coccinea 8phaeralcea coccinea Stipa viridula Rosa woodsii Linum p e r e n n e Melilotus officinalis Psoralea esculenta Erigeron pumilus Chrysopsis villosa
threadleaf sedge sun sedge needleleaf sedge HoOds phlox c o m m o n dandelion Missouri milkvetch yellow prairie violet Holboel! rockcress c o m m o n purple lilac plains wallflower tineleafed milkvetch prairie onion Lambert loco prairie junegrass white penstemon needleandthread yelk~w salsify Kentucky bluegrass scarlet gaura scarlet globemallow green needlegrass woods rose perennial flax yellow sweetclover breadroot scurf pea low fleabane hairy goldenaster
Apr. Apt, Apr. Apr. May May May May May May May May May Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun, Jun. Jun.
Apr. 8 Apr. 8 Apr. 8 Apr. 15 May 3 May 3 May 4 May 6 May 13 May 7 May 13 May 11 May 12 May 25 May 25 May 25 May 29 May 30 Jun. 1 Jun. 1 Jun. 1 Jun. 2 Jun. 2 Jun. 5 Jun. 5 Jun. 7 Jun. 10
Apr. Apr. Apr. May May May May May May May May May May Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun.
13 13 19 26 10 10 11 12 19 20 20 20 22 1 3 3 6 7 8 9 9 10 12 13 13 14 14
14 14 28 8 21 22 22 20 23 29 29 29 29 10 12 12 13 15 12 19 22 19 20 20 19 19 19
44 45 46 47 48 49 50 51 52 53
43
28 29 30 31 32 33 34 35 36 37 38 39 40 41 42
Agropyron smithii Polygala alba Opuntia polyacantha Achillea millefolium Potentilla pennsylvanica Aristida longiseta Lactuca pulchella Cirsium undulatum Erigeron strigosus Echinacea pallida Psoralea argophylla Ratibida columnifera Lygodesmia juncea Muhlenbergia cuspidata Bouteloua curtipendula S y mp ho ricarpos occidentalis Petalostemon purpureum Calamovilfa longifolia Bouteloua gracilis Schizachyrium scoparium Solidago missouriensis Solidago mollis Liatris punctata Haplopappus spinulosus Aster falcatus Aster oblongifolius western snowberry p u r p l e prairieclover prairie s a n d r e e d blue g r a m a little b l u e s t e m Missouri g o l d e n r o d velvety g o l d e n r o d dotted gayfeather ironplant goldenweed w h i t e p r a i r i e aster aromatic aster
western wheatgrass white polygala plains p r i c k l y p e a r common yarrow Pennsylvania cinquefoil red threeawn chicory lettuce wavyleaf thistle rough fleabane pale e c h i n a c e a silverleaf s c u r f p e a prairie c o n e f l o w e r rush skeletonplant stoneyhills Muhly sideoats grama
19 21 22 22 23 24 25 27 28 30 4 7 7 8 12
Jul. 13 Jul. 14 Jul. 19 Jul. 20 Jul. 30 Jul. 30 Jul. 31 Aug. 5 Aug. 14 Aug. 27 Aug. 29
Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jul. Jul. Jul. Jul. Jul.
14 14 14 14 18 14 18 21 25 25 25 30 1 30 2 Jul. 6 Jul. 6 Jul. 10 Jul. 9 Jul. 22 Jul. 28 Jul. 26 Jul. 28 Aug. 12 Aug. 20 Aug. 25
Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jul. Jun. Jul. Jul. 18 Jul. 22 Jul. 29 Jul. 31 Aug. 12 Aug. 5 Aug. 5 Aug. 12 Aug. 19 Sep. 1 Sep. 1
J u n . 24 J u n . 26 J u n . 30 J u n . 30 J u n . 26 Jul. 3 Jul. 1 Jul. 5 Jul. 7 Jul. 5 Jul. 1 0 Jul. 11 Jul. 12 Jul. 15 Jul. 22
194
let equal the threshold before the mean temperature was calculated. E x c e p t i o , 2 was when the maximum temperature was above the o p t i m u m temperature, the maximum was let equal the o p t i m u m before the mean temperature was calculated. The fifth method, thermal days (nonlinear temperature response), was the accumulation of daily temperature indices (TI}, which are an exponential expression (Rickman et al., 1975): T I = exp ~ A T ( ( T o
-- T ) / T ) :
(3)
where T is degrees Kelvin temperature (°C + 273), and To is an assumed o p t i m u m temperature for development. In eq.3, A is a constant which determines the temperature where T I equals 0.01. If for example, we assume that developmental rate at 0°C (273°K) is 0.01 of the developmental rate at o p t i m u m temperature, and o p t i m u m temperature for development is 25°C (298°K), then T = 273°K (0°C); T I = 0.01; T o = 298°K (25°C); and then the equation is solved for A. In the above example, A equals 1.02338. We can then substitute A into the eq.3, and solve the equation for any temperature. The value of T I varies from 0 to 1; its values for mean temperatures from 0 to 35°C are illustrated in Fig.1 for two assumed optima, 20 and 25°C, with a threshold temperature of 0°C. In calculating thermal days both mean daffy temperature: T = (Tmax + Tmin)/2
(4)
and effective daylight temperature {Went, 1957): T = Tmax
1/4 ( T m a x - Train)
(5)
were compared. The sixth method, degree--solar (linear) days, was the product of degree days (remainder) (linear temperature response) and daily solar radiation in langley/day divided b y 750 {linear response). The seventh method, thermal--solar (linear) days, was a product of thermal days (nonlinear temperature response) and daily solar radiation in langley/day divided by 750 (linear response). The eighth method, degree--solar (nonlinear) days, was a product of degree days (remainder) and solar radiation index (SI), which is a nonlinear response (Fitzpatrick and Nix, 1970): S I = 1.0 -- (exp -- 3.5X)
(6)
where X is daily solar radiation in langley/day divided by 750. The ninth method, thermal--solar (nonlinear) days, was a product of thermal days (nonlinear temperature response) and solar radiation index iS/), as calculated in eq.6. Linear and nonlinear factoring of solar radiation are illustrated in Fig.2. A c o m m o n base unit was needed to compare how well the nine methods accounted for variation in flowering dates. Therefore, a normalizing procedure
195
1.00
I
W0.75
~
I
-
0.50
-
~0.25
0
0
5
15
25
35
TEMPERATURE(c)
Fig.1. Temperature indices used in calculating thermal days with a nonlinear temperature response (e.g., 20/0 = 20°C optimum/0°C threshold temperature).
1.0(
I
I
/
~
~
0.7~ "X W d~ zH m 0.50
< _J 0
~
Linear
0.25
C
I
1
I
0.25 0-50 0.75 1.00 TOTAL SOLAR RADIATION(ly/day)/750
Fig.2. Linear and nonlinear solar radiation indices used in calculating thermal-solar days.
196
was used to convert the 4-year average accumulated meteorological indice {accumulated from 1 March until flowering) for each method and for each species back to an appropriate calendar date for each year. The differences between this estimated date and the actual flowering date for each species each year were analyzed using a one-way analysis of variance, with species as treatments and years as replications. The accuracy of each method was thus, directly determined in days. The threshold temperature between --10 and 10°C that most accurately related degree days (remainder), degree hours (duration-summation), NOAAdegree days, and thermal days to the flowering-date variation was determined by a m e t h o d described by Arnold {1959). All 53 species were first tested as a group to determine which threshold temperature produced the lowest standard deviation (SD). Not all species, however, will have the same best threshold temperature. Instead of testing each species individually, the 53 species were divided into two groups -- the earliest 26 species to flower {flowering April through 14 June) and the latest 27 species to flower (flowering 15 June through August). Also o p t i m u m temperatures of 20 and 25°C were tested with thermal days and a 25°C o p t i m u m tested with NOAA-degree days to determine which one most accurately related flowering dates of each group to air temperature. Flowering dates must be estimated as soon as possible before flowering to help agriculturists plan their work. Therefore, instead of accumulating meteorological indices until each species flowered, meteorological indices were accumulated from 1 March until a preselected number was reached near either mid-April or mid-May (method 10). Analyses were then made to determine if there was a constant number: of calendar days from that time until the 40 species flowered (those species flowering from June through August). Flowering dates of any one of the first thirteen species to flower were tested ( m e t h o d 11) to see if they could be used as an index to determine the flowering dates of the remaining 40 species (those flowering from June through August). This group of 40 species was selected so that any o n e ' o f the thirteen species would flower before any one of the 40 species. The same 40 species were used for all comparisons (both for index species and preselected meteorological indices) so that the accuracy of each method was judged against the same standard. RESULTS A N D DISCUSSION
Flowering dates varied widely each year (Figs.3 and 4). In 1967 and 1968, average flowering dates of all 53 species were 6.3 and 2.4 days later than the 4-year average, and in 1969 =and 1971, 5.3 and 3.4 days earlier than the 4-year average. During a given year, flowering dates o f each species, were n o t consistently earlier than the 4.year average. ~ g early April 1967, species flowered near their 4,year average, bu~ cold t e m p ~ a t m s d ~ g late April and early May delayed flowering of all late-flowering species that year. During
197 I
I
5040~30-
19
~J20
~
1 7
-
-
10
-
--
0
APR
MAY
I
JUNE
I
JULY
I
AUG
Fig. 3. V a r i a t i o n o f f l o w e r i n g dates of 53 species b e t w e e n 1 9 6 7 a n d 1 9 7 1 n e a r Sidney, Montana.
I
5040rY w
Z
W2o
u m w
-
6
~
S
1968
-
0._ u")
100
~ APR
MAY
I
JUNE
I
JULY
I
AUG
I
Fig.4. V a r i a t i o n o f f l o w e r i n g dates o f 53 species b e t w e e n 1 9 6 8 a n d 1 9 6 9 near Sidney, Montana.
198 April and early May 1968, individual species flowered earlier than their 4-year average, but after mid-June individual species flowered later than their 4-year average. A c c u m u l a t i o n o f t e m p e r a t u r e radices ( m e t h o d s 1 - - 5 )
The 20-day moving average of maximum temperature (method 1) was poorly related to the flowering dates of all 53 species ( S D = 11.4 days), earliest 26 ( S D = 10.2), and latest 27 species ( S D = 11.4) to flower. The thermal days (method 5) was the most accurate method in relating temperature to the flowering dates of all 53 species ( S D = 4.1 days), earliest 26 ( S D = 3.8), and latest 27 species ( S D = 4.2) to flower (Figs.5, 6, 7). An optimum temperature of 25°C most accurately related thermal days to the flowering dates of all 53 species and the earliest 26 species to flower, however, an optimum of 20°C was more accurate for the latest 27 species to flower. Using "effective daylight temperature" (Went, 1957) with thermal days (25°C optimum) instead of mean temperature increased the S D ( F i g . 5 ) . Lindsey and Newman (1956) and Arnold (1960) reported that the degree hours (duration-summation) (method 3) was more accurate than degree days (remainder) (method 2) in calculating temperature indices when the minimum temperature was less than the threshold temperature. However, the accuracy of the degree hours (duration-summation) only equaled that of the degree days (remainder) in relating the flowering dates of plants at Sidney to temperature. The NOAA-degree days (method 4) with threshold temperatures from --5 to 9°C with optimum of 25°C was at least one day less accurate than thermal days, degree days (remainder), and degree hours (duration-summation) methods. Using an optimum of 20°C with a threshold of 5°C reduced its accuracy ( S D = 6.1) for all 53 species. Using an optimum of 30°C or no optimum with a threshold of 5°C still did not improve its accuracy ( S D = 5.6) for all 53 species. Using a threshold temperature of --5°C with an optimum of 30°C only slightly improved its accuracy ( S D = 5.2) for all 53 species. The threshold temperature which most accurately relates temperature indices to flowering dates varied with the method used and the group of species tested (Figs.5, 6, 7). The best threshold temperature for the degree day (remainder) and degree hours (duration-summation) were between 2 and 5°C for all 53 species, and earliest 26 species to flower. It was between 4 and 7~C for the latest 27 species to flower. Thermal days required a threshold temperature between --5 and 10°C for all three groups of species with one exception. When an optimum of 20°C was used with the 27 latest flowering species a threshold temperature of +5°C was required. All methods of accumulating temperature indices (methods 2, 3, 5) except the NOAA-degree day (method 4) produced S D that were within 0.3 days of each other in accounting for the variation among flowering dates for all 53 species, earliest 26, or latest 27 species to flower (Figs.5, 6 and 7). The best
199 I
•~ 8 >, oZ7 >6 0
I
I
I
I
ALL 53 SPECIES
o
/
-
~- ~ Degree Days (Remainder) ._ ..~ Degree Hours(D-S) / m----mNOAA-Degree Days / //~ o o M25/X Thermal Days / ///o o 0 M20/X Thermal Days NIP / , / / e.----o Ed25/X Thermal Days / J - " ~ / - - t .
.
.
.
.
• -- ~m.--~
o
./o/L
--
/
,/,'
z
_
~
N4
-
I
-10
I
I
I
I
-5 0 5 THRESHOLD TEME (c)
10
Fig. 5. Effects of various threshold temperatures in calculating degree days (remainder), degree hours (duration-summation), NOAA-degree days, and thermal days in accounting for the yearly variation of flowering dates of 53 species during 4 years (M = mean, E D = effective daylight temperature, 2 0 / = o p t i m u m temperature, / X = various threshold temperatures).
I
8 -
z 7 0 ~: .~ 6 rnLd
I
1
I
26 EARLIEST SPECIES
/
J
f%
I
/ X
-
Degree Days (Remainder) ,Degree Hours(D-S) // / ~----6 m-- --m NOAA-Degree Days / o ~ / / o o M25/X Thermal Days o o M 2 0 / X Thermal Days / / / . ~ . . J~" ..i/"
~5 o
. . . .
-
,~_,- ?
z
1,1
I
-10
I
I
I
-5 0 5 THRESHOLD TEMP.(c)
I
10
Fig.6. Effects of various threshold temperatures in calculating degree days (remainder), degree hours (duration-summation), NOAA-degree days, and thermal days in accounting for the yearly variation of~flowering dates of the 26 earliest flowering species during 4 years.
200
I ~.8 )~ c~
27
~
LATEST
_~ D e g r e e
T
[
I
SPECIES
~ ~
<~
6
o
o M25/X
Thermal
Days
- o
o M20/X
Thermal
Days
w
~
/
Days (Remainder)
b---, D e g r e e Hours (D-S) z 7 - ~_.4 NOAA-Degree Days o
o
-
o .u-/
~ Z . . . . ""- -'~'-'- -0- -0 ,~
4
-
1 -10
1
1
I
-5 0 5 THRESHOLD TEMP.(c)
I
~
10
Fig. 7. Effects of various threshold temperatures in calculating degree days (remainder), degree hours (duration~ummation), NOAA-degree days, and thermal days in accounting for the yearly variation of flowering dates of the 27 latest flowering species during 4 years.
overall method was the thermal days (25°C optimum) (method 5), because it could use a wider latitude of threshold temperatures without significantly increasing the SD. This would be especially important in working with both early- and late-flowering species, because early-flowering species require a lower threshold temperature than do late-floweringspecies. The date that the earliest26 species flowered (SD = 7.4 days) varied more from their 4-year average than did that for all 53 species (SD = 7.0 days), or did the latest 27 species (SD = 6.7 days). Thermal days (25°C optimum) (method 5) accounted for 4 9 % of the variation in flowering dates of the earliest 26 species to flower, 4 1 % of the variation for all 53 species,and only 3 4 % of the variation for the latest27 species to flower.
Accumulation of temperature times solar radiation indices (methods 6--9) Including solar radiation factored either linearly or nonlinearly with either degree days (remainder) called ~ l a r days (method 6) or with thermal days called thermal--solar days (method 7) generally did not account for any m o r e o f t h e variation a m o n g flowering dates t h a n did t e m p e r a t u r e alone (degree days (remainder) or thermal days) (Table II). Including solar radiation
201 TABLE II Relationship of temperature and temperature times solar radiation to the yearly variation among flowering dates of three groups of species Indices
Method No.
All 53 species 2°C (. . . . . . . .
Earliest 26 species
Latest 27 species
2°C 5°C threshold temp . . . . . . . . .
)
(Standard deviation, days) Degree days (remainder) Degree-solar (linear) days Degree-solar (nonlinear) days
2 6 8
4.3 4.9 4.5
5 7 9
threshold temp. --4°C --5°C +5°C (Standard deviation, days) 4.4 3.9 4.2 4.5 4.3 4.3 4.4 4.1 4.1
5 7 9
threshold temp. --8°C --8°C --4°C (Standard deviation, days) 4.1 3.8 4.4 4.7 4.2 5.4 4.3 4.0 4.7
(Optimum 20°C) Thermal days Thermal-solar (linear) days Thermal-solar (nonlinear) days ( Optimum 25°C) Thermal days Thermal-solar (linear days) Thermal-solar (nonlinear) days
4.0 4.5 4.2
4.5 5.6 4.8
f a cto r ed linearly generally increased the SD by over 0.5 days and including solar radiation f a c t o r e d nonlinearly generally increased SD by only 0.1 days. Only in one case did including solar radiation (thermal--solar days) reduce the SD (0.1 day), and this was for the latest 27 species. However, Caprio (1974) f o u n d th at when he included solar radiation with degree days t hat it helped to a c co u n t for th e date when c o m m o n purple lilac flowered in the United States.
Preselected index days (method 10) Flowering o f 40 species (those t hat flowered June through August) varied 6.9 days ab o u t their m ean flowering date. The accumulation of thermal days with o p t i m a t e m p e r a t u r e s of 20 and 25°C until mid-May significantly a c c o u n t e d f o r 1.2 and 1.4 days of the 6.9 day variation, respectively, and thus a c c o u n t e d for 20% o f the flowering-date variation (Table III). The accumulation of degree days (remainder) or thermal days until mid-April did n o t significantly a c c o u n t for the variation of flowering dates of the 40 species (6.9 days SD). A ccum ul a t i on o f degree days (remainder) or thermal days until mid-April did n o t a c c o u n t for the low temperatures in late April o f
202 TABLE III Relationship of when a preselected number of degree days (remainder) or thermal days was reached sometime near mid-April or raid-May to the yearly variation of flowering dates of 40 species (flowering during June through August) Methods
Degree days (remainder) Thermal days M20/5 M25/--4
Mid-April
Mid-May
Indices accumulated
Standard deviation
Indices accumulated
Standard deviation
(no.)
(days)
(no.)
(days)
50
5.9 ns I
175
6.1 ns
],4 3.4
6.7 ns 7.0 ns
6.4 9.9
5.7* 5.5*
1 Column values are significant (*) or nonsignificant (ns) as compared with the 6.9 days variation in flowering dates among 40 species for 4 years.
1967 that delayed flowering of all species after this date. The best threshold temperature, determined for the 27 latest species to flower (Fig.7), was used in accumulating degree days (remainder) and thermal days for the 40 species.
Index plants (method 11 ) The date that any o f the four species flowering in April -- threadleaf sedge, sun sedge, needleleaf sedge, Hood's phlox -- was poorly related to when the 40 species would flower and worse ~than using the mean flowering date. In using the flowering date of these four species to estimate flowering dates of the 40 species, the SD's ranged from 8.5 to 12.2 days where as the SD of mean-flowering date of these same 40 species was only 6.9 days. The date that any o f the four species flowered in early May c o m m o n dandelion, Missouri milkvetch, Holboell rockcress, c o m m o n purple lilac -- was poorly related to when the 40 species would flower SD ranged from 6.5 to 7.7 days. The dates that any one of the five species flowered in late May (Table IV) -- yellow prairie violet, plairm wallflower, tineltmfed milkvetch, prairie onion, Lambert loco -- were good indicators of when the 40 species would flower 1--3 months later. The flowenng dates o f any of these five species estimated the flowering dates of the 40 species within 4.8--5.2 days (SD). However, they still a c c o u n t e d for only 25% o f the flowering~ate variation. This study suggested that the date a species flower in early April could n o t be used to accurately indicate when a species would flower 1 or 3 months later, as was suggested b y Budd and Campbell (1959). In this study, low
203 TABLEIV Relationship of floweringdates of thirteen indexspecies (flowering duringApril or May) to the yearlyvariation of floweringdatesof 40 species (floweringduringJune through August) Plant no.
Common name
Standard deviation (days)
1 2 3 4
Species flowering in April: threadleaf sedge sun sedge needleleaf sedge Hoods phlox
8.5* l 8.5* 12.2"* 10.7"*
5 6 7 8 9 10 11 12 13
Species flowering in May: common dandelion Missouri milkvetch yellow prairie violet Holboell rockcress common purple lilac plains wallflower tineleafed milkvetch prairie onion Lambert loco
6.9 ns 7.3 ns 5.2* * 7.7 ns 6.5 ns 5.1"* 5.0* * 4.8" * 4.8**
1 Column values are significant (*), highly significant (**), non-significant (ns) as compared with the 6.9 days variation in flowering dates of 40 species for 4 years.
t e m p e r a t u r e s in late A p r i l o f 1 9 6 7 d e l a y e d t h e f l o w e r i n g o f all s p e c i e s f l o w e r ing after this date.
CONCLUSIONS The accumulation of thermal days was the most accurate of the eleven methods tested of accounting for the variation of flowering dates among species each year. It estimated flowering dates within 4.1 days SD for all 53 species, 3.8 days for the earliest 26, and 4.2 days for the latest 27 species to flower. However, the degree days (remainder) was simpler to calculate and resulted in only 0.3 days (SD) less accuracy. The addition of solar radiation with temperature did not account for any more variation among flowering dates. Using the flowering date of plains wallflower, tineleaf milkvetch, prairie onion, or Lambert loco resulted in only a 1.0 day (SD) loss of accuracy as compared with accumulating degree days (remainder) until each species flowered. T h u s , t h e d a t e t h a t a s e l e c t e d i n d e x s p e c i e s f l o w e r e d was t h e s i m p l e s t a n d probably most practical method that agriculturists and range managers could
204 use t o b a s e t h e i r m a n a g e m e n t d e c i s i o n s . H o w e v e r , t h e y will h a v e t o w a i t u n t i l late May to use an i n d e x species in m a k i n g their decisions.
REFERENCES Arnold, C. Y., 1959. The determination and significance of the base temperature in a linear heat unit system. Proc. Am. Soc. Hortic. Sci., 74: 430--445. Arnold, C. Y., 1960. Maximum--minimum temperatures as a basis for computing heat units. Proc. Am. Soc. Hortic. Sci., 76: 682--692. Bassett, I. J., Holmes, R. M. and MacKay, K. H., 1961. Phenology of several plant species at Ottawa, Ontario, and an examination of the influence of air temperatures. Can. J. Plant Sci., 41: 643--652. Blaisdell, J. P., 1958. Seasonal development and yield of native plants on the upper Snake River plains and their relation to certain climatic factors. U.S. Dep. Agric. Tech. Bull., 1190, 68 pp. Brown, D. M., 1960. Soybean ecology. I. Development-temperature relationships from controlled environment studies. Agron. J., 52: 493--496. Budd, A C. and Campbell, J. B., 1959. Flowering sequence of a local flora. J. Range Manage., 12: 127--132. Caprio, J. M., 1974. The solar thermal unit concept in problems related to plant development and potential evapotranspiration. In: H. Lieth (Editor), Phenology and Seasonality Modeling. Springer-Verlag, New York, pp. 353--364. Criddle, N., 1927. A calendar of flowers. Can. Field Nat., 41: 48--55. Fitzpatrick, E. A. and Nix, H. A., 1970. The climatic factor in Australian grassland ecology. In: R. M. Moore (Editor), Australian Grasslands. Australian National University Press, Canberra, pp. 3--26. Gilmore, Jr., E. C. and Rogers, J. S., 1958. Heat units as a method of measuring maturity in corn. Agron. J., 50: 611--615. Holmes, R. IVL and Robertson, G. W., 1959. Heat units and crop growth. Can. Dep. Agric. Publ. 1042, 31 pp. Hulbert, L. C., 1963. Gates' phenotogical records of 132 plants at Manhattan, Kansas, 1926--1955. Trans. Kansas Acad. Sci., 66: 82--106. Leopold, A. and Jones, S. E., 1947. A phenological record for Sauk and Dane counties, Wisconsin, 1935--1945. Ecol. Monogr., 17: 81--122. Lindsey, A. A. and Newman, J. E., 1956. Use of official weather data in spring time-temperature analysis of an Indiana phenological record. Ecology, 37: 812--823. Madariaga, F. J. and Knott, J. E., 1951. Temperature summations in relation to lettuce growth. Proc. Am. Soc. Hortic. Sei., 58: 147--152. Rickman, 1~ W., Ramig, R. E. and Allmaras, R. R., 197 5. Modeling dry matter accumulation in dryland winter wheat. Agron. J., 67: 283--289. Smith, J. W., 1915. II. Phenological dates and meteorological data recorded by Thomas Mikesell between 1873 and 1912 at Wauseon, Ohio. U.S. Weather Bur. Monthly Weather Rev. Suppl. No. 2, pp. 23---93. Stevens, O. A., 1956. Flowering dates of weeds in North Dakota. N. D. Agric. Exp. Stn, (Bimo.) Bull., 18: 209--213. Went, F. W., 1957. Experimental control of plant growth. Chron. Bot., Waltham, Mass., 343 pp. Wielgolaski, F. E., 1974. Phenology in Agriculture. In: H. Lieth (Editor), Phenology and Seasonality Modeling. Springer-Verlag, New York, pp. 369--381.
189
©Elsevier Scientific Publishing Company, Amsterdam -- Printed in The Netherlands
RELATIONSHIP BETWI~EN METEOROLOGICAL MEASUREMENTS FLOWERING OF INDEX SPECIES TO FLOWERING OF 53 PLANT SPECIES*
AND
L A R R Y M. WHITE
Range Scientist, USDA-SEA, Agricultural Research, Northern Plains Soil and Water Research Center, Sidney, Montana 59270 (U.S.A.) (Received January 5, 1978; accepted after revision April 28, 1978) ABSTRACT White, L. M., 1979. Relationship between meteorological measurements and flowering of index species to flowering of 53 plant species. Agric. Meteorol., 20: 189--204. Agriculturists and range managers need advanced knowledge o f when a plant will reach a specific developmental stage to plan when to apply herbicides, to begin grazing season, to change pastures in a grazing system, and to harvest forage. Relationship between flowering dates of 53 plant species and accumulation of temperature, temperature plus solar radiation, and the flowering of index species was studied for four years near Sidney, Montana Accumulation o f thermal days (a nonlinear heat unit system which discounts mean temperatures over an o p t i m u m ) was the most accurate of eleven methods tested in accounting for variation among flowering dates. It accounted for 49% of the variation for early-flowering species but only accounted for 34% of the variation for late-flowering species. However, the degree days (remainder) was simpler to calculate and resulted in only 0.3-day standard deviation (SD) loss of accuracy. The degree days (remainder) was equal with the degree hours (duration-summation) in accuracy and both were a day more accurate than the NOAA-degree days. The 20-day moving average of m ax i m u m air temperatures was the least accurate of the eleven methods in accounting for variation of flowering dates. The addition o f solar-radiation with temperature did not account for any more o f the variation among flowering dates. The date that a selected index species flowered was the simplest and probably the most practical method of estimating flowering dates if a 1.0 day (SD) loss of accuracy was acceptable. Knowing the time that a selected index species flowered made possible estimating within five days (SD) the flowering dates of 40 species one to three months earlier.
INTRODUCTION Phenology (the science concerned with the relationship of periodic biological events with seasonal climatic changes) can assist agriculturists and range managers in making management decisions. With advance knowledge of when plant species will reach a specific developmental stage, plans can be *Contribution: USDA-SEA, Agricultural Research, NorthernPlains Soiland Water Research Center, in cooperationwith the Montana Agricultural ExperimentStation, Journal Series No. 799.
190
made to: (1) apply herbicides; (2) begin grazing season; (3) change pastures in a grazing system; and (4) harvest forage. Plant flowering, the developmental stage considered herein, is undoubtedly affected by the entire soil and aerial environment. However, temperature largely controls plant growth and development (Wielgolaski, 1974). The summation of positive temperatures or heat units (degree days) (remainder) above a threshold or "base temperature" has been used for many years to determine maturity date of cultivated plants (Holmes and Robertson, 1959). The degree days (remainder) under calculates degree days when the minimum temperature is below the threshold temperature. Various methods have been developed to correct this error (Lindsey and Newman, 1956; Gilmore and Rogers, 1958; Arnold, 1960). The degree days (remainder) also assumes a linear relationship between plant development and all temperatures above the threshold temperature. Changing the threshold thus changes the weight of each degree above the threshold and does not recognize an optimum temperature for plant development. Various methods have been developed to discount high temperatures and recognize an optimum temperature (Madariaga and Knott, 1951; Gilmore and Rogers, 1958; Brown, 1960). Few studies have been conducted that related the accumulation of temperature to growth and development of North American plant species. Lindsey and Newman (1956) found that flowering of 24 species near Bluffton, Indiana, was closely related to degree days (remainder). However, they had to vary the threshold temperature between 5 and 10°C, depending on the species. Blaisdell (1958), working near Dubois, Idaho, found that the mean March-through-May temperature was highly correlated with flowering of eight species. Bassett et al. (1961) found that flowering of some species near Ottawa, Ontario, was related to variation in average maximum air temperature, others to variation in average minimum air temperatures, still others were not markedly influenced by air temperature. Several studies reported on the average flowering dates for many North American plant species, but they have not attempted to relate meteorological measurements to plant development (Smith, 1915; Criddle, 1927; Leopold and Jones, 1947; Stevens, 1956; Budd and Campbell, 1959; Hulbert, 1963). The objective of this study was to determine the relationship between temperature, temperature plus solar radiation, and flowering of index plant species to flowering of 53 plant species during four years. M A T E R I A L S AND METHODS
The study was conducted on a mixed-prairie, glaciated-plains, sandy-range site on a Williams loam soil (fine-loamy mixed, Typic Axgiborolls) 4 km northwest of Sidney, Montana at an elevation of 665 m. The study site was a uniform area 100 by 100 m that gently sloped to the southwest. Frost-free period averages 122 days; January and July average temperatures are --13 and 20°C, respectively. Average annual precipitation is 34 cm, 44% of which
191
occurs during April through June when most native species make their greatest growth. For the s t u d y years (1967, 1968, 1969, 1971), the total Aprilthrough-June precipitation departed from normal by 6, --1, 8 and --2 cm, respectively. Each year, the s t u d y site was visited three or four times weekly from April through August and the flowering dates of 53 selected native range species were recorded (Table I). Forbs and shrubs were considered as flowering when 10% of the plants within the study area had at least one flower. Grasses and sedges were considered as flowering when 10% of their first heads were fully visible. Heading was used for grasses and sedges, rather than anthesis, as the criterion, because some species, like needleandthread and green needlegrass, self-pollinate and anthers never become visible. Maximum and minimum shelter temperatures and precipitation were obtained at the site. Solar radiation data were taken from official records for Glasgow, Montana, the nearest location (190 km west-northwest of the site). The climate resembles that at Sidney, elevation is only 34 m higher, and although daily solar radiation varies somewhat, only small errors should be introduced in the calculations. Flowering dates were separately related to nine different ways of accumulating daily meteorological measurements from the first of March each year. The first method, was the 20-day moving average of maximum air temperatures. The second method, degree days (remainder) was the simple accumulation of daily mean air temperatures above a given threshold (linear temperature response). The third method, degree hours (duration-summation) (Lindsey and Newman, 1956) was the accumulation of degree hours (DH) and when the minimum temperature (Tmin) was less than the threshold temperature (Tthre), they were calculated by eq.l: DH
=
12 (Tmax -- Tthre) 2 T m a x - Tmin
(1)
where Tmax = m a x i m u m temperature (linear temperature response). When the minimum temperature was equal or greater than the threshold temperature, degree hours (duration-summation) were calculated by eq.2: DH
=
24 (Tmax-2 Tmin)__ ~ Tthre
(2)
The fourth method, called "NOAA-degree days" is the method used to calculate degree days in the National Weekly Weather and Crop Bulletin that is published by the United States Department of Agriculture and the National Oceanic and Atmospheric Administration (NOAA). This m e t h o d accumulates the degrees that the mean temperature was above the threshold temperature with t w o exceptions (non-linear temperature response). Exception 1 was when the minimum temperature was below the threshold, the minimum was
~D b~
TABLE I Average, earliest and latest flowering dates of 53 plant species for 4 years near Sidney, Montana Plant No.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 I9 20 21 22 23 24 25 26 27
Scientific name
C o m m o n name
Average flowering date
Earliest flowering date
Latest flowering date
Carex filifolia Carex heliophila Carex eleocharis Phlox hoodii Taraxacu m o fficina le Astragalusmi~ouriensis Viola nuttallii Arabis holboellii Sy~nga vuigaris Erysimum asperum Astragalus pectinatus Alliumtextile Oxytropis lambertii Koeleria cristata Penstemon albidus Stipa comata Tragopogon dubius Poa pratensis Gaura coccinea 8phaeralcea coccinea Stipa viridula Rosa woodsii Linum p e r e n n e Melilotus officinalis Psoralea esculenta Erigeron pumilus Chrysopsis villosa
threadleaf sedge sun sedge needleleaf sedge HoOds phlox c o m m o n dandelion Missouri milkvetch yellow prairie violet Holboel! rockcress c o m m o n purple lilac plains wallflower tineleafed milkvetch prairie onion Lambert loco prairie junegrass white penstemon needleandthread yelk~w salsify Kentucky bluegrass scarlet gaura scarlet globemallow green needlegrass woods rose perennial flax yellow sweetclover breadroot scurf pea low fleabane hairy goldenaster
Apr. Apt, Apr. Apr. May May May May May May May May May Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun, Jun. Jun.
Apr. 8 Apr. 8 Apr. 8 Apr. 15 May 3 May 3 May 4 May 6 May 13 May 7 May 13 May 11 May 12 May 25 May 25 May 25 May 29 May 30 Jun. 1 Jun. 1 Jun. 1 Jun. 2 Jun. 2 Jun. 5 Jun. 5 Jun. 7 Jun. 10
Apr. Apr. Apr. May May May May May May May May May May Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun.
13 13 19 26 10 10 11 12 19 20 20 20 22 1 3 3 6 7 8 9 9 10 12 13 13 14 14
14 14 28 8 21 22 22 20 23 29 29 29 29 10 12 12 13 15 12 19 22 19 20 20 19 19 19
44 45 46 47 48 49 50 51 52 53
43
28 29 30 31 32 33 34 35 36 37 38 39 40 41 42
Agropyron smithii Polygala alba Opuntia polyacantha Achillea millefolium Potentilla pennsylvanica Aristida longiseta Lactuca pulchella Cirsium undulatum Erigeron strigosus Echinacea pallida Psoralea argophylla Ratibida columnifera Lygodesmia juncea Muhlenbergia cuspidata Bouteloua curtipendula S y mp ho ricarpos occidentalis Petalostemon purpureum Calamovilfa longifolia Bouteloua gracilis Schizachyrium scoparium Solidago missouriensis Solidago mollis Liatris punctata Haplopappus spinulosus Aster falcatus Aster oblongifolius western snowberry p u r p l e prairieclover prairie s a n d r e e d blue g r a m a little b l u e s t e m Missouri g o l d e n r o d velvety g o l d e n r o d dotted gayfeather ironplant goldenweed w h i t e p r a i r i e aster aromatic aster
western wheatgrass white polygala plains p r i c k l y p e a r common yarrow Pennsylvania cinquefoil red threeawn chicory lettuce wavyleaf thistle rough fleabane pale e c h i n a c e a silverleaf s c u r f p e a prairie c o n e f l o w e r rush skeletonplant stoneyhills Muhly sideoats grama
19 21 22 22 23 24 25 27 28 30 4 7 7 8 12
Jul. 13 Jul. 14 Jul. 19 Jul. 20 Jul. 30 Jul. 30 Jul. 31 Aug. 5 Aug. 14 Aug. 27 Aug. 29
Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jul. Jul. Jul. Jul. Jul.
14 14 14 14 18 14 18 21 25 25 25 30 1 30 2 Jul. 6 Jul. 6 Jul. 10 Jul. 9 Jul. 22 Jul. 28 Jul. 26 Jul. 28 Aug. 12 Aug. 20 Aug. 25
Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jun. Jul. Jun. Jul. Jul. 18 Jul. 22 Jul. 29 Jul. 31 Aug. 12 Aug. 5 Aug. 5 Aug. 12 Aug. 19 Sep. 1 Sep. 1
J u n . 24 J u n . 26 J u n . 30 J u n . 30 J u n . 26 Jul. 3 Jul. 1 Jul. 5 Jul. 7 Jul. 5 Jul. 1 0 Jul. 11 Jul. 12 Jul. 15 Jul. 22
194
let equal the threshold before the mean temperature was calculated. E x c e p t i o , 2 was when the maximum temperature was above the o p t i m u m temperature, the maximum was let equal the o p t i m u m before the mean temperature was calculated. The fifth method, thermal days (nonlinear temperature response), was the accumulation of daily temperature indices (TI}, which are an exponential expression (Rickman et al., 1975): T I = exp ~ A T ( ( T o
-- T ) / T ) :
(3)
where T is degrees Kelvin temperature (°C + 273), and To is an assumed o p t i m u m temperature for development. In eq.3, A is a constant which determines the temperature where T I equals 0.01. If for example, we assume that developmental rate at 0°C (273°K) is 0.01 of the developmental rate at o p t i m u m temperature, and o p t i m u m temperature for development is 25°C (298°K), then T = 273°K (0°C); T I = 0.01; T o = 298°K (25°C); and then the equation is solved for A. In the above example, A equals 1.02338. We can then substitute A into the eq.3, and solve the equation for any temperature. The value of T I varies from 0 to 1; its values for mean temperatures from 0 to 35°C are illustrated in Fig.1 for two assumed optima, 20 and 25°C, with a threshold temperature of 0°C. In calculating thermal days both mean daffy temperature: T = (Tmax + Tmin)/2
(4)
and effective daylight temperature {Went, 1957): T = Tmax
1/4 ( T m a x - Train)
(5)
were compared. The sixth method, degree--solar (linear) days, was the product of degree days (remainder) (linear temperature response) and daily solar radiation in langley/day divided b y 750 {linear response). The seventh method, thermal--solar (linear) days, was a product of thermal days (nonlinear temperature response) and daily solar radiation in langley/day divided by 750 (linear response). The eighth method, degree--solar (nonlinear) days, was a product of degree days (remainder) and solar radiation index (SI), which is a nonlinear response (Fitzpatrick and Nix, 1970): S I = 1.0 -- (exp -- 3.5X)
(6)
where X is daily solar radiation in langley/day divided by 750. The ninth method, thermal--solar (nonlinear) days, was a product of thermal days (nonlinear temperature response) and solar radiation index iS/), as calculated in eq.6. Linear and nonlinear factoring of solar radiation are illustrated in Fig.2. A c o m m o n base unit was needed to compare how well the nine methods accounted for variation in flowering dates. Therefore, a normalizing procedure
195
1.00
I
W0.75
~
I
-
0.50
-
~0.25
0
0
5
15
25
35
TEMPERATURE(c)
Fig.1. Temperature indices used in calculating thermal days with a nonlinear temperature response (e.g., 20/0 = 20°C optimum/0°C threshold temperature).
1.0(
I
I
/
~
~
0.7~ "X W d~ zH m 0.50
< _J 0
~
Linear
0.25
C
I
1
I
0.25 0-50 0.75 1.00 TOTAL SOLAR RADIATION(ly/day)/750
Fig.2. Linear and nonlinear solar radiation indices used in calculating thermal-solar days.
196
was used to convert the 4-year average accumulated meteorological indice {accumulated from 1 March until flowering) for each method and for each species back to an appropriate calendar date for each year. The differences between this estimated date and the actual flowering date for each species each year were analyzed using a one-way analysis of variance, with species as treatments and years as replications. The accuracy of each method was thus, directly determined in days. The threshold temperature between --10 and 10°C that most accurately related degree days (remainder), degree hours (duration-summation), NOAAdegree days, and thermal days to the flowering-date variation was determined by a m e t h o d described by Arnold {1959). All 53 species were first tested as a group to determine which threshold temperature produced the lowest standard deviation (SD). Not all species, however, will have the same best threshold temperature. Instead of testing each species individually, the 53 species were divided into two groups -- the earliest 26 species to flower {flowering April through 14 June) and the latest 27 species to flower (flowering 15 June through August). Also o p t i m u m temperatures of 20 and 25°C were tested with thermal days and a 25°C o p t i m u m tested with NOAA-degree days to determine which one most accurately related flowering dates of each group to air temperature. Flowering dates must be estimated as soon as possible before flowering to help agriculturists plan their work. Therefore, instead of accumulating meteorological indices until each species flowered, meteorological indices were accumulated from 1 March until a preselected number was reached near either mid-April or mid-May (method 10). Analyses were then made to determine if there was a constant number: of calendar days from that time until the 40 species flowered (those species flowering from June through August). Flowering dates of any one of the first thirteen species to flower were tested ( m e t h o d 11) to see if they could be used as an index to determine the flowering dates of the remaining 40 species (those flowering from June through August). This group of 40 species was selected so that any o n e ' o f the thirteen species would flower before any one of the 40 species. The same 40 species were used for all comparisons (both for index species and preselected meteorological indices) so that the accuracy of each method was judged against the same standard. RESULTS A N D DISCUSSION
Flowering dates varied widely each year (Figs.3 and 4). In 1967 and 1968, average flowering dates of all 53 species were 6.3 and 2.4 days later than the 4-year average, and in 1969 =and 1971, 5.3 and 3.4 days earlier than the 4-year average. During a given year, flowering dates o f each species, were n o t consistently earlier than the 4.year average. ~ g early April 1967, species flowered near their 4,year average, bu~ cold t e m p ~ a t m s d ~ g late April and early May delayed flowering of all late-flowering species that year. During
197 I
I
5040~30-
19
~J20
~
1 7
-
-
10
-
--
0
APR
MAY
I
JUNE
I
JULY
I
AUG
Fig. 3. V a r i a t i o n o f f l o w e r i n g dates of 53 species b e t w e e n 1 9 6 7 a n d 1 9 7 1 n e a r Sidney, Montana.
I
5040rY w
Z
W2o
u m w
-
6
~
S
1968
-
0._ u")
100
~ APR
MAY
I
JUNE
I
JULY
I
AUG
I
Fig.4. V a r i a t i o n o f f l o w e r i n g dates o f 53 species b e t w e e n 1 9 6 8 a n d 1 9 6 9 near Sidney, Montana.
198 April and early May 1968, individual species flowered earlier than their 4-year average, but after mid-June individual species flowered later than their 4-year average. A c c u m u l a t i o n o f t e m p e r a t u r e radices ( m e t h o d s 1 - - 5 )
The 20-day moving average of maximum temperature (method 1) was poorly related to the flowering dates of all 53 species ( S D = 11.4 days), earliest 26 ( S D = 10.2), and latest 27 species ( S D = 11.4) to flower. The thermal days (method 5) was the most accurate method in relating temperature to the flowering dates of all 53 species ( S D = 4.1 days), earliest 26 ( S D = 3.8), and latest 27 species ( S D = 4.2) to flower (Figs.5, 6, 7). An optimum temperature of 25°C most accurately related thermal days to the flowering dates of all 53 species and the earliest 26 species to flower, however, an optimum of 20°C was more accurate for the latest 27 species to flower. Using "effective daylight temperature" (Went, 1957) with thermal days (25°C optimum) instead of mean temperature increased the S D ( F i g . 5 ) . Lindsey and Newman (1956) and Arnold (1960) reported that the degree hours (duration-summation) (method 3) was more accurate than degree days (remainder) (method 2) in calculating temperature indices when the minimum temperature was less than the threshold temperature. However, the accuracy of the degree hours (duration-summation) only equaled that of the degree days (remainder) in relating the flowering dates of plants at Sidney to temperature. The NOAA-degree days (method 4) with threshold temperatures from --5 to 9°C with optimum of 25°C was at least one day less accurate than thermal days, degree days (remainder), and degree hours (duration-summation) methods. Using an optimum of 20°C with a threshold of 5°C reduced its accuracy ( S D = 6.1) for all 53 species. Using an optimum of 30°C or no optimum with a threshold of 5°C still did not improve its accuracy ( S D = 5.6) for all 53 species. Using a threshold temperature of --5°C with an optimum of 30°C only slightly improved its accuracy ( S D = 5.2) for all 53 species. The threshold temperature which most accurately relates temperature indices to flowering dates varied with the method used and the group of species tested (Figs.5, 6, 7). The best threshold temperature for the degree day (remainder) and degree hours (duration-summation) were between 2 and 5°C for all 53 species, and earliest 26 species to flower. It was between 4 and 7~C for the latest 27 species to flower. Thermal days required a threshold temperature between --5 and 10°C for all three groups of species with one exception. When an optimum of 20°C was used with the 27 latest flowering species a threshold temperature of +5°C was required. All methods of accumulating temperature indices (methods 2, 3, 5) except the NOAA-degree day (method 4) produced S D that were within 0.3 days of each other in accounting for the variation among flowering dates for all 53 species, earliest 26, or latest 27 species to flower (Figs.5, 6 and 7). The best
199 I
•~ 8 >, oZ7 >6 0
I
I
I
I
ALL 53 SPECIES
o
/
-
~- ~ Degree Days (Remainder) ._ ..~ Degree Hours(D-S) / m----mNOAA-Degree Days / //~ o o M25/X Thermal Days / ///o o 0 M20/X Thermal Days NIP / , / / e.----o Ed25/X Thermal Days / J - " ~ / - - t .
.
.
.
.
• -- ~m.--~
o
./o/L
--
/
,/,'
z
_
~
N4
-
I
-10
I
I
I
I
-5 0 5 THRESHOLD TEME (c)
10
Fig. 5. Effects of various threshold temperatures in calculating degree days (remainder), degree hours (duration-summation), NOAA-degree days, and thermal days in accounting for the yearly variation of flowering dates of 53 species during 4 years (M = mean, E D = effective daylight temperature, 2 0 / = o p t i m u m temperature, / X = various threshold temperatures).
I
8 -
z 7 0 ~: .~ 6 rnLd
I
1
I
26 EARLIEST SPECIES
/
J
f%
I
/ X
-
Degree Days (Remainder) ,Degree Hours(D-S) // / ~----6 m-- --m NOAA-Degree Days / o ~ / / o o M25/X Thermal Days o o M 2 0 / X Thermal Days / / / . ~ . . J~" ..i/"
~5 o
. . . .
-
,~_,- ?
z
1,1
I
-10
I
I
I
-5 0 5 THRESHOLD TEMP.(c)
I
10
Fig.6. Effects of various threshold temperatures in calculating degree days (remainder), degree hours (duration-summation), NOAA-degree days, and thermal days in accounting for the yearly variation of~flowering dates of the 26 earliest flowering species during 4 years.
200
I ~.8 )~ c~
27
~
LATEST
_~ D e g r e e
T
[
I
SPECIES
~ ~
<~
6
o
o M25/X
Thermal
Days
- o
o M20/X
Thermal
Days
w
~
/
Days (Remainder)
b---, D e g r e e Hours (D-S) z 7 - ~_.4 NOAA-Degree Days o
o
-
o .u-/
~ Z . . . . ""- -'~'-'- -0- -0 ,~
4
-
1 -10
1
1
I
-5 0 5 THRESHOLD TEMP.(c)
I
~
10
Fig. 7. Effects of various threshold temperatures in calculating degree days (remainder), degree hours (duration~ummation), NOAA-degree days, and thermal days in accounting for the yearly variation of flowering dates of the 27 latest flowering species during 4 years.
overall method was the thermal days (25°C optimum) (method 5), because it could use a wider latitude of threshold temperatures without significantly increasing the SD. This would be especially important in working with both early- and late-flowering species, because early-flowering species require a lower threshold temperature than do late-floweringspecies. The date that the earliest26 species flowered (SD = 7.4 days) varied more from their 4-year average than did that for all 53 species (SD = 7.0 days), or did the latest 27 species (SD = 6.7 days). Thermal days (25°C optimum) (method 5) accounted for 4 9 % of the variation in flowering dates of the earliest 26 species to flower, 4 1 % of the variation for all 53 species,and only 3 4 % of the variation for the latest27 species to flower.
Accumulation of temperature times solar radiation indices (methods 6--9) Including solar radiation factored either linearly or nonlinearly with either degree days (remainder) called ~ l a r days (method 6) or with thermal days called thermal--solar days (method 7) generally did not account for any m o r e o f t h e variation a m o n g flowering dates t h a n did t e m p e r a t u r e alone (degree days (remainder) or thermal days) (Table II). Including solar radiation
201 TABLE II Relationship of temperature and temperature times solar radiation to the yearly variation among flowering dates of three groups of species Indices
Method No.
All 53 species 2°C (. . . . . . . .
Earliest 26 species
Latest 27 species
2°C 5°C threshold temp . . . . . . . . .
)
(Standard deviation, days) Degree days (remainder) Degree-solar (linear) days Degree-solar (nonlinear) days
2 6 8
4.3 4.9 4.5
5 7 9
threshold temp. --4°C --5°C +5°C (Standard deviation, days) 4.4 3.9 4.2 4.5 4.3 4.3 4.4 4.1 4.1
5 7 9
threshold temp. --8°C --8°C --4°C (Standard deviation, days) 4.1 3.8 4.4 4.7 4.2 5.4 4.3 4.0 4.7
(Optimum 20°C) Thermal days Thermal-solar (linear) days Thermal-solar (nonlinear) days ( Optimum 25°C) Thermal days Thermal-solar (linear days) Thermal-solar (nonlinear) days
4.0 4.5 4.2
4.5 5.6 4.8
f a cto r ed linearly generally increased the SD by over 0.5 days and including solar radiation f a c t o r e d nonlinearly generally increased SD by only 0.1 days. Only in one case did including solar radiation (thermal--solar days) reduce the SD (0.1 day), and this was for the latest 27 species. However, Caprio (1974) f o u n d th at when he included solar radiation with degree days t hat it helped to a c co u n t for th e date when c o m m o n purple lilac flowered in the United States.
Preselected index days (method 10) Flowering o f 40 species (those t hat flowered June through August) varied 6.9 days ab o u t their m ean flowering date. The accumulation of thermal days with o p t i m a t e m p e r a t u r e s of 20 and 25°C until mid-May significantly a c c o u n t e d f o r 1.2 and 1.4 days of the 6.9 day variation, respectively, and thus a c c o u n t e d for 20% o f the flowering-date variation (Table III). The accumulation of degree days (remainder) or thermal days until mid-April did n o t significantly a c c o u n t for the variation of flowering dates of the 40 species (6.9 days SD). A ccum ul a t i on o f degree days (remainder) or thermal days until mid-April did n o t a c c o u n t for the low temperatures in late April o f
202 TABLE III Relationship of when a preselected number of degree days (remainder) or thermal days was reached sometime near mid-April or raid-May to the yearly variation of flowering dates of 40 species (flowering during June through August) Methods
Degree days (remainder) Thermal days M20/5 M25/--4
Mid-April
Mid-May
Indices accumulated
Standard deviation
Indices accumulated
Standard deviation
(no.)
(days)
(no.)
(days)
50
5.9 ns I
175
6.1 ns
],4 3.4
6.7 ns 7.0 ns
6.4 9.9
5.7* 5.5*
1 Column values are significant (*) or nonsignificant (ns) as compared with the 6.9 days variation in flowering dates among 40 species for 4 years.
1967 that delayed flowering of all species after this date. The best threshold temperature, determined for the 27 latest species to flower (Fig.7), was used in accumulating degree days (remainder) and thermal days for the 40 species.
Index plants (method 11 ) The date that any o f the four species flowering in April -- threadleaf sedge, sun sedge, needleleaf sedge, Hood's phlox -- was poorly related to when the 40 species would flower and worse ~than using the mean flowering date. In using the flowering date of these four species to estimate flowering dates of the 40 species, the SD's ranged from 8.5 to 12.2 days where as the SD of mean-flowering date of these same 40 species was only 6.9 days. The date that any o f the four species flowered in early May c o m m o n dandelion, Missouri milkvetch, Holboell rockcress, c o m m o n purple lilac -- was poorly related to when the 40 species would flower SD ranged from 6.5 to 7.7 days. The dates that any one of the five species flowered in late May (Table IV) -- yellow prairie violet, plairm wallflower, tineltmfed milkvetch, prairie onion, Lambert loco -- were good indicators of when the 40 species would flower 1--3 months later. The flowenng dates o f any of these five species estimated the flowering dates of the 40 species within 4.8--5.2 days (SD). However, they still a c c o u n t e d for only 25% o f the flowering~ate variation. This study suggested that the date a species flower in early April could n o t be used to accurately indicate when a species would flower 1 or 3 months later, as was suggested b y Budd and Campbell (1959). In this study, low
203 TABLEIV Relationship of floweringdates of thirteen indexspecies (flowering duringApril or May) to the yearlyvariation of floweringdatesof 40 species (floweringduringJune through August) Plant no.
Common name
Standard deviation (days)
1 2 3 4
Species flowering in April: threadleaf sedge sun sedge needleleaf sedge Hoods phlox
8.5* l 8.5* 12.2"* 10.7"*
5 6 7 8 9 10 11 12 13
Species flowering in May: common dandelion Missouri milkvetch yellow prairie violet Holboell rockcress common purple lilac plains wallflower tineleafed milkvetch prairie onion Lambert loco
6.9 ns 7.3 ns 5.2* * 7.7 ns 6.5 ns 5.1"* 5.0* * 4.8" * 4.8**
1 Column values are significant (*), highly significant (**), non-significant (ns) as compared with the 6.9 days variation in flowering dates of 40 species for 4 years.
t e m p e r a t u r e s in late A p r i l o f 1 9 6 7 d e l a y e d t h e f l o w e r i n g o f all s p e c i e s f l o w e r ing after this date.
CONCLUSIONS The accumulation of thermal days was the most accurate of the eleven methods tested of accounting for the variation of flowering dates among species each year. It estimated flowering dates within 4.1 days SD for all 53 species, 3.8 days for the earliest 26, and 4.2 days for the latest 27 species to flower. However, the degree days (remainder) was simpler to calculate and resulted in only 0.3 days (SD) less accuracy. The addition of solar radiation with temperature did not account for any more variation among flowering dates. Using the flowering date of plains wallflower, tineleaf milkvetch, prairie onion, or Lambert loco resulted in only a 1.0 day (SD) loss of accuracy as compared with accumulating degree days (remainder) until each species flowered. T h u s , t h e d a t e t h a t a s e l e c t e d i n d e x s p e c i e s f l o w e r e d was t h e s i m p l e s t a n d probably most practical method that agriculturists and range managers could
204 use t o b a s e t h e i r m a n a g e m e n t d e c i s i o n s . H o w e v e r , t h e y will h a v e t o w a i t u n t i l late May to use an i n d e x species in m a k i n g their decisions.
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